Volume 19, Issue 4 (12-2025)
مرتع 2025, 19(4): 405-420 |
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Amrollahi Jalalabadi A, Rastgar S, Rezaei A, Naghipour A A. Predicting the impact of climate change on the distribution of the medicinal plant Teucrium polium L. in the rangelands of Kerman province. مرتع 2025; 19 (4) :405-420
URL: http://rangelandsrm.ir/article-1-1317-en.html
URL: http://rangelandsrm.ir/article-1-1317-en.html
Department of Rangeland Management, Faculty of Natural Resources, Sari University of Agricultural Sciences and Natural Resources, Sari
Abstract: (332 Views)
Background and Objective: Climate is one of the primary drivers of plant species diversity and distribution and plays a crucial role in shaping their biological characteristics. Consequently, climate change can induce substantial shifts in the distribution ranges of plant species by altering their tolerance limits and the environmental factors governing their geographical expansion. Predicting the impacts of future climate change on the distribution of valuable plant species is therefore essential for effective management, conservation planning, and threat assessment. This study aimed to predict the effects of climate change on the current and future geographical distribution of the medicinal plant Teucrium polium L. in the rangelands of Kerman Province, Iran.
Methodology: During the spring and summer of 2024, six reference habitats of T. polium in Kerman Province were surveyed. Presence records of the species were collected through field observations, and their geographical coordinates were recorded using a GPS device. Species distribution modeling was conducted for two time periods: the baseline (current) period and a future period (2050). The environmental variables used in the modeling process included 19 bioclimatic variables, three physiographic variables, and land-use data for the study area.
To predict the future distribution of T. polium, two general circulation models (GCMs)—HadGEM3-GC31-LL and MRI-ESM2-0—were applied under two shared socioeconomic pathway scenarios (SSP245 and SSP585). Pearson’s correlation analysis was performed in SPSS software to assess multicollinearity among all environmental variables. From each pair of variables with a correlation coefficient exceeding 0.80, one variable was removed based on expert judgment, resulting in the selection of 10 variables for model input. The maximum entropy (MaxEnt) model was used to predict the current and future potential distribution of the species. The relative importance of environmental variables was evaluated using the Jackknife test. Habitat suitability maps for the present and 2050 were then compared using geographic information system (GIS) techniques to identify areas of habitat expansion, contraction, and persistence. Model performance was assessed using the area under the receiver operating characteristic curve (AUC).
Results: The AUC values obtained (AUC > 0.9) indicated excellent predictive performance of the MaxEnt model, with an AUC score of 0.974 for T. polium habitat distribution in the study area. The most influential variables contributing to habitat suitability were slope percentage, precipitation of the coldest quarter, and mean temperature of the coldest quarter. According to projections based on the HadGEM3-GC31-LL model, by 2050, suitable habitats for T. polium are expected to decrease by 68.08% under the SSP245 scenario and by 68.93% under the SSP585 scenario, while newly suitable habitats are projected to increase by 98.54% and 106.90%, respectively. Similarly, projections from the MRI-ESM2-0 model indicated a reduction of suitable habitats by 43.94% under SSP245 and 50.73% under SSP585, alongside increases of 84.21% and 99.72% in newly suitable habitats, respectively.
Conclusion: The results suggest that Teucrium polium possesses adaptive capacity to drought stress through various defense mechanisms, including reduced plant height, accumulation of proline and proteins in aerial parts, and responsiveness to key environmental factors such as slope, precipitation of the coldest quarter, and mean temperature of the coldest quarter. These traits may enable the species to colonize new suitable habitats under future climate conditions. Overall, the findings highlight the importance of incorporating climate change projections into conservation and management strategies for medicinal plant species in arid and semi-arid rangelands.
Methodology: During the spring and summer of 2024, six reference habitats of T. polium in Kerman Province were surveyed. Presence records of the species were collected through field observations, and their geographical coordinates were recorded using a GPS device. Species distribution modeling was conducted for two time periods: the baseline (current) period and a future period (2050). The environmental variables used in the modeling process included 19 bioclimatic variables, three physiographic variables, and land-use data for the study area.
To predict the future distribution of T. polium, two general circulation models (GCMs)—HadGEM3-GC31-LL and MRI-ESM2-0—were applied under two shared socioeconomic pathway scenarios (SSP245 and SSP585). Pearson’s correlation analysis was performed in SPSS software to assess multicollinearity among all environmental variables. From each pair of variables with a correlation coefficient exceeding 0.80, one variable was removed based on expert judgment, resulting in the selection of 10 variables for model input. The maximum entropy (MaxEnt) model was used to predict the current and future potential distribution of the species. The relative importance of environmental variables was evaluated using the Jackknife test. Habitat suitability maps for the present and 2050 were then compared using geographic information system (GIS) techniques to identify areas of habitat expansion, contraction, and persistence. Model performance was assessed using the area under the receiver operating characteristic curve (AUC).
Results: The AUC values obtained (AUC > 0.9) indicated excellent predictive performance of the MaxEnt model, with an AUC score of 0.974 for T. polium habitat distribution in the study area. The most influential variables contributing to habitat suitability were slope percentage, precipitation of the coldest quarter, and mean temperature of the coldest quarter. According to projections based on the HadGEM3-GC31-LL model, by 2050, suitable habitats for T. polium are expected to decrease by 68.08% under the SSP245 scenario and by 68.93% under the SSP585 scenario, while newly suitable habitats are projected to increase by 98.54% and 106.90%, respectively. Similarly, projections from the MRI-ESM2-0 model indicated a reduction of suitable habitats by 43.94% under SSP245 and 50.73% under SSP585, alongside increases of 84.21% and 99.72% in newly suitable habitats, respectively.
Conclusion: The results suggest that Teucrium polium possesses adaptive capacity to drought stress through various defense mechanisms, including reduced plant height, accumulation of proline and proteins in aerial parts, and responsiveness to key environmental factors such as slope, precipitation of the coldest quarter, and mean temperature of the coldest quarter. These traits may enable the species to colonize new suitable habitats under future climate conditions. Overall, the findings highlight the importance of incorporating climate change projections into conservation and management strategies for medicinal plant species in arid and semi-arid rangelands.
Keywords: General circulation models, Maximum Entropy model, Species distribution modeling, Emission scenarios, Suitable habitat
Type of Study: Research |
Subject:
Special
Received: 2025/04/17 | Accepted: 2025/08/5 | Published: 2025/12/1
Received: 2025/04/17 | Accepted: 2025/08/5 | Published: 2025/12/1
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